Softwr

Databases · head to head

OpenSearch vs Zilliz

OpenSearch logo

OpenSearch

Databases

Open-source search and analytics suite forked from Elasticsearch

From
Free
Rated
-
Zilliz logo

Zilliz

Databases

Managed vector database and vector lakebase for AI applications

From
Free
Rated
-

The short version

  • Each has a real cost: OpenSearch diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one; Zilliz pricing structure not publicly disclosed, requires sales contact
  • They diverge on capability: OpenSearch covers Full-text search, Zilliz covers Vector indexing.

Where they differ

Only the attributes on which OpenSearch and Zilliz actually diverge.

Attributes where OpenSearch and Zilliz differ
AttributeOpenSearchZilliz
Pricing modelOpen source, no licence fee; managed services billed separatelycontact-sales
PlatformsLinux, Docker, Kubernetes, Self-hostedCloud, Self-hosted
FoundedUnknown2017

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in OpenSearch

  • Full-text search
  • OpenSearch Dashboards
  • Log analytics
  • Vector search

Only in Zilliz

  • Vector indexing
  • Distributed architecture
  • SQL interface
  • Tensor support
  • Real-time search
  • Cloud-native
  • Open-source compatible

What people use each for

The jobs each tool is most often brought in to do.

OpenSearch

  • Log and observability storage where an Apache-2.0 licence is a requirementnot Zilliz
  • Replacing Elasticsearch after the licence change without changing architecturenot Zilliz
  • Search plus analytics on one cluster rather than two systemsnot Zilliz

Zilliz

  • Build retrieval-augmented generation (RAG) systemsnot OpenSearch
  • Implement semantic search over documentsnot OpenSearch
  • Create multimodal search with text and imagesnot OpenSearch
  • Power recommendation engines with vector similaritynot OpenSearch
  • Enable similarity search on user embeddingsnot OpenSearch

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

OpenSearch

  • Diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • Operationally heavy in the way Elasticsearch is: cluster sizing, shard strategy and JVM tuning are ongoing work
  • Smaller ecosystem of third-party tooling than Elasticsearch, which most integrations still target first
  • Overkill for plain application search, where a dedicated search engine is far simpler

Zilliz

  • Pricing structure not publicly disclosed, requires sales contact
  • Operational complexity for self-hosted Milvus deployments
  • Learning curve for those unfamiliar with vector databases
  • Limited built-in analytics compared to some alternatives

Pricing, plan by plan

OpenSearch

Free
  • OpenSearchFree
    • Full functionality
    • Self-hosted
    • No usage limits

Zilliz

Free

No published plan breakdown. See the Zilliz review.

Which should you pick?

Choose OpenSearch if

  • You need full-text search.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want opensearch dashboards.

Choose Zilliz if

  • You need vector indexing.
  • You want to start without paying.
  • You work on Cloud, Self-hosted.
  • You also want distributed architecture.

Questions people ask

Is OpenSearch or Zilliz better?
Neither clearly leads. OpenSearch starts at Free and Zilliz at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, OpenSearch or Zilliz?
OpenSearch starts at Free and Zilliz at Free.
Does OpenSearch or Zilliz run on more platforms?
OpenSearch runs on Linux, Docker, Kubernetes, Self-hosted. Zilliz runs on Cloud, Self-hosted.
Can I use OpenSearch for free?
Both have a free tier, so you can try either at no cost before committing.
What is OpenSearch best used for?
OpenSearch is most often used for log and observability storage where an apache-2.0 licence is a requirement, replacing elasticsearch after the licence change without changing architecture, search plus analytics on one cluster rather than two systems. Of those, log and observability storage where an apache-2.0 licence is a requirement and replacing elasticsearch after the licence change without changing architecture are not what Zilliz is typically brought in for.
What can OpenSearch do that Zilliz cannot?
OpenSearch covers Full-text search, OpenSearch Dashboards, Log analytics, Vector search. Zilliz covers Vector indexing, Distributed architecture, SQL interface, Tensor support.

Answered from the vendors’ own pages

OpenSearch: Is OpenSearch free?

Yes, Apache 2.0 licensed under the Linux Foundation. Amazon OpenSearch Service is a paid managed option.

Zilliz: What is the difference between Milvus and Zilliz Cloud?

Milvus is the open-source vector database that you can self-host. Zilliz Cloud is the fully managed service built on Milvus that removes operational overhead and handles scaling automatically.

Source
OpenSearch: Why does OpenSearch exist?

Elastic moved Elasticsearch off the Apache 2.0 licence in 2021. AWS forked the last Apache-licensed version, and the project now sits under the Linux Foundation.

Zilliz: How many vectors can Zilliz handle?

Milvus and Zilliz Cloud can store and search billions of vectors through their distributed architecture that separates storage and compute layers.

Source
OpenSearch: Is OpenSearch compatible with Elasticsearch?

It was at the 7.10 fork point. Both have developed independently since, so compatibility weakens with every release and should be verified for the features you use.

Zilliz: Is Milvus open-source?

Yes, Milvus is open-source under the Apache License 2.0 and is part of the LF AI & Data Foundation.

Source
Zilliz: What pricing does Zilliz Cloud offer?

Zilliz Cloud pricing is not publicly listed and requires contacting their team to discuss your specific scale and use case requirements.

Source
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